C

Capital One

Issues credit cards and runs a consumer bank

Applied Researcher 4 - AI Foundations, VLM Customization

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Currently has or is in the process of obtaining a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field, to be obtained by the scheduled start date; alternatively, an MS in one of these fields plus two years of applied research experience.
  • Have a deep understanding of the foundations of AI methodologies.
  • Have experience building large deep learning models for language, images, events, or graphs, and expertise in one or more of training optimization, self-supervised learning, robustness, explainability, or reinforcement learning from human feedback.
  • Demonstrate an engineering mindset through a track record of delivering models at scale in training data and inference volumes.
  • Have experience delivering libraries, platform-level code, or solution-level code to existing products.
  • Have a track record of generating high-quality ideas or improving existing machine-learning ideas, demonstrated by accomplishments such as first-author publications or projects.
  • Be able to own and pursue a research agenda, including selecting impactful research problems and autonomously carrying out long-running projects.
  • Have hands-on experience developing AI foundation models and solutions using open-source tools and cloud-computing platforms.
  • Be comfortable with open-source languages.
  • For the LLM focus: have a PhD focused on natural language processing, or a master's degree with five years of industrial natural-language-processing research experience.
  • For the LLM focus: have multiple publications related to pre-training large language models, such as technical reports of pretrained LLMs, self-supervised learning techniques, or model pre-training optimization.
  • For the LLM focus: have been a member of a team that trained a large language model from scratch with 10 billion or more parameters and 500 billion or more tokens.
  • For the LLM focus: have publications in deep-learning theory and publications at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.
  • For the fine-tuning focus: have a PhD focused on guiding LLMs with further tasks, such as supervised fine-tuning, instruction tuning, dialogue fine-tuning, or parameter tuning.
  • For the fine-tuning focus: demonstrate knowledge of transfer learning, model adaptation, and model guidance.
  • For the fine-tuning focus: have experience deploying a fine-tuned large language model.
  • For the data-preparation focus: have publications studying tokenization, data quality, dataset curation, or labeling.
  • For the data-preparation focus: have contributed to a major open-source corpus or open-source libraries for data quality, dataset curation, or labeling.
  • Demonstrate the ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks.
  • Have experience designing controlled experiments and documenting reproducibility results for internal or public research.

Responsibilities

  • Partner with data scientists, software engineers, machine-learning engineers, and product managers to deliver AI-powered products that change how customers interact with their money.
  • Use technologies including PyTorch, AWS Ultraclusters, Hugging Face, and Lightning to uncover insights in large volumes of numeric and textual data.
  • Build AI foundation models through design, training, evaluation, validation, and implementation.
  • Conduct applied research to advance emerging AI developments into customer experiences.
  • Translate complex technical work into business goals.
  • Collaborate with senior researchers to prepare internal technical reports or conference submissions summarizing novel methods or findings.

Desired Qualifications

  • Preferred PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field.

About the Company

Capital One

Issues credit cards and runs a consumer bank

Capital One runs a consumer and commercial bank that issues credit cards, takes deposits, and finances cars and businesses. Its Venture travel cards and Quicksilver cash-back cards let customers earn rewards on everyday spending, while its online banking tools manage payments and savings. Customers use checking and savings accounts through an app, branches, and cash machines, and commercial clients use treasury tools to manage company cash. The bank earns interest on loans and fees from banking and card transactions, with customer deposits helping fund its lending operations. Capital One was founded in 1994 and has its headquarters in McLean, Virginia.

Company size
10,001+
Company stage
IPO
Headquarters
McLean, VA
Founded
1994

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